The invention relates to signal modulators, and more particularly to modulation techniques useful for converting an analog signal into a digital signal.
Today's information age would not have been possible without the existence of digital technology. The huge amount of storage, communications, and information processing that now goes on continuously throughout the world relies on the fact that representation of information can be reduced to ones and zeroes. Moore's law, stating that every 18 months the amount of transistors per area is doubled, or the cost is halved, still seems to remain valid. Yet, our daily lives are filled with analog signals; that is, signals that are continuous in time and continuous in amplitude. Nyquist has shown that signals whose frequency bandwidth is limited can be made time-discrete (i.e., represented only by values associated with distinct points in time) if the rate of sampling is sufficiently large. In addition, signals can be made amplitude discrete (i.e., represented only by values selected from a fixed set of values, eliminating any possibility of any values lying “in-between” any of the values in the fixed set) by quantizing to discrete levels. In applications such as communications, the number of bits in the quantization is determined by the required signal-to-noise ratio (SNR) conditions since quantization adds quantization noise.
It can be appreciated, then, that the interface between the analog world and the digital world is crucial for the success of digitally processing analog information. In the past, a lot of attention has been paid to analog-to-digital (A/D) converters and A/D modulators. Depending on the required speed (bandwidth of the input signal) and the required SNR, different A/D concepts can be used. Examples include successive approximation A/D, flash A/D, delta modulation, and sigma-delta modulation. These well-known techniques will now be briefly discussed.
Successive approximation is a low cost concept that can be used when the number of bits per sample has to be large. However conversion per sample takes quite a long time and the concept is not attractive for input signals with a large bandwidth.
Flash converters are extremely fast, but have high power consumption and are expensive.
Delta modulation and sigma-delta modulation techniques have become very popular as they use simple implementations and show fairly good performance. In delta modulation, the input signal is followed in a step-wise fashion: for every detected increase in the input signal, the output is increased by a fixed step size; for every detected decrease in the input signal, the output is likewise decreased by a fixed step size. Delta modulation is limited in bandwidth and amplitude because of slope overload. Slope overload occurs when the magnitude of the rise (or fall) in the input signal is larger than the steps can follow. Using larger steps compromises the SNR at smaller signal levels because the quantization levels are coarser.
Sigma-delta modulators do not have this limitation. In these modulators, the average of the binary output represents the input level. Sigma-delta modulators require a large oversampling rate in order to reduce the variation in this average.
Sigma-delta modulators are commonly used for high-performance audio and video applications. They have a few disadvantages though. For one thing, a feedback loop is used in sigma-delta modulators. The circuitry in the loop runs at the oversampling rate and can therefore consume quite a lot of power. Moreover, the loop can become unstable and may exhibit limit cycles. Additionally, the oversampling rate must be much higher than the bandwidth of the signal being sampled. Because of limits on how high the oversampling rate can be, the signal bandwidth cannot be extremely large. Furthermore, since the sigma-delta modulation introduces noise shaping, moving noise into the higher frequency area, rather extensive low-pass filtering in the digital domain is required to prevent aliasing during the down-sampling. (Down-sampling is a process whereby the number of samples representing a signal is reduced, as though the signal had been originally sampled at a slower sampling rate.)